





import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bart import BartTokenizer


lowercase :			str     		=    logging.get_logger(__name__)


lowercase :			Union[str, Any]     		=    {"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt""", """tokenizer_file""": """tokenizer.json"""}

# See all BART models at https://huggingface.co/models?filter=bart
lowercase :			Optional[int]     		=    {
    """vocab_file""": {
        """facebook/bart-base""": """https://huggingface.co/facebook/bart-base/resolve/main/vocab.json""",
        """facebook/bart-large""": """https://huggingface.co/facebook/bart-large/resolve/main/vocab.json""",
        """facebook/bart-large-mnli""": """https://huggingface.co/facebook/bart-large-mnli/resolve/main/vocab.json""",
        """facebook/bart-large-cnn""": """https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json""",
        """facebook/bart-large-xsum""": """https://huggingface.co/facebook/bart-large-xsum/resolve/main/vocab.json""",
        """yjernite/bart_eli5""": """https://huggingface.co/yjernite/bart_eli5/resolve/main/vocab.json""",
    },
    """merges_file""": {
        """facebook/bart-base""": """https://huggingface.co/facebook/bart-base/resolve/main/merges.txt""",
        """facebook/bart-large""": """https://huggingface.co/facebook/bart-large/resolve/main/merges.txt""",
        """facebook/bart-large-mnli""": """https://huggingface.co/facebook/bart-large-mnli/resolve/main/merges.txt""",
        """facebook/bart-large-cnn""": """https://huggingface.co/facebook/bart-large-cnn/resolve/main/merges.txt""",
        """facebook/bart-large-xsum""": """https://huggingface.co/facebook/bart-large-xsum/resolve/main/merges.txt""",
        """yjernite/bart_eli5""": """https://huggingface.co/yjernite/bart_eli5/resolve/main/merges.txt""",
    },
    """tokenizer_file""": {
        """facebook/bart-base""": """https://huggingface.co/facebook/bart-base/resolve/main/tokenizer.json""",
        """facebook/bart-large""": """https://huggingface.co/facebook/bart-large/resolve/main/tokenizer.json""",
        """facebook/bart-large-mnli""": """https://huggingface.co/facebook/bart-large-mnli/resolve/main/tokenizer.json""",
        """facebook/bart-large-cnn""": """https://huggingface.co/facebook/bart-large-cnn/resolve/main/tokenizer.json""",
        """facebook/bart-large-xsum""": """https://huggingface.co/facebook/bart-large-xsum/resolve/main/tokenizer.json""",
        """yjernite/bart_eli5""": """https://huggingface.co/yjernite/bart_eli5/resolve/main/tokenizer.json""",
    },
}

lowercase :			str     		=    {
    """facebook/bart-base""": 1_0_2_4,
    """facebook/bart-large""": 1_0_2_4,
    """facebook/bart-large-mnli""": 1_0_2_4,
    """facebook/bart-large-cnn""": 1_0_2_4,
    """facebook/bart-large-xsum""": 1_0_2_4,
    """yjernite/bart_eli5""": 1_0_2_4,
}





class 					A__       (				__A      ):




   """simple docstring"""



   __A  :							Any			    =    VOCAB_FILES_NAMES
   __A  :							Tuple			    =    PRETRAINED_VOCAB_FILES_MAP
   __A  :							Optional[Any]			    =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   __A  :							int			    =    ['''input_ids''', '''attention_mask''']
   __A  :							Any			    =    BartTokenizer

   def __init__(   self   ,    lowercase=None   ,    lowercase=None   ,    lowercase=None   ,    lowercase="replace"   ,    lowercase="<s>"   ,    lowercase="</s>"   ,    lowercase="</s>"   ,    lowercase="<s>"   ,    lowercase="<unk>"   ,    lowercase="<pad>"   ,    lowercase="<mask>"   ,    lowercase=False   ,    lowercase=True   ,    **lowercase   ,    )     ->		Any:







          '''simple docstring'''

          super().__init__(
              UpperCamelCase__   ,    UpperCamelCase__   ,    tokenizer_file=UpperCamelCase__   ,    errors=UpperCamelCase__   ,    bos_token=UpperCamelCase__   ,    eos_token=UpperCamelCase__   ,    sep_token=UpperCamelCase__   ,    cls_token=UpperCamelCase__   ,    unk_token=UpperCamelCase__   ,    pad_token=UpperCamelCase__   ,    mask_token=UpperCamelCase__   ,    add_prefix_space=UpperCamelCase__   ,    trim_offsets=UpperCamelCase__   ,    **UpperCamelCase__   ,    )

          a__		:      List[Any]					=							json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__())
          if pre_tok_state.get('add_prefix_space'   ,    UpperCamelCase__) != add_prefix_space:
                 a__		:      List[Any]					=							getattr(UpperCamelCase__   ,    pre_tok_state.pop('type'))
                 a__		:      Any					=							add_prefix_space
                 a__		:      Tuple					=							pre_tok_class(**UpperCamelCase__)

          a__		:      Tuple					=							add_prefix_space

          # the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
          a__		:      Dict					=							'post_processor'
          a__		:      Union[str, Any]					=							getattr(self.backend_tokenizer   ,    UpperCamelCase__   ,    UpperCamelCase__)
          if tokenizer_component_instance:
                 a__		:      int					=							json.loads(tokenizer_component_instance.__getstate__())

                 # The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
                 if "sep" in state:
                        a__		:      Optional[Any]					=							tuple(state['sep'])
                 if "cls" in state:
                        a__		:      Union[str, Any]					=							tuple(state['cls'])

                 a__		:      Optional[Any]					=							False

                 if state.get('add_prefix_space'   ,    UpperCamelCase__) != add_prefix_space:
                        a__		:      Optional[int]					=							add_prefix_space
                        a__		:      Dict					=							True

                 if state.get('trim_offsets'   ,    UpperCamelCase__) != trim_offsets:
                        a__		:      int					=							trim_offsets
                        a__		:      List[str]					=							True

                 if changes_to_apply:
                        a__		:      Dict					=							getattr(UpperCamelCase__   ,    state.pop('type'))
                        a__		:      List[str]					=							component_class(**UpperCamelCase__)
                        setattr(self.backend_tokenizer   ,    UpperCamelCase__   ,    UpperCamelCase__)

   @property
   def 				__lowercase						(   self)     ->		Any:







          '''simple docstring'''

          if self._mask_token is None:
                 if self.verbose:
                        logger.error('Using mask_token, but it is not set yet.')
                 return None
          return str(self._mask_token)

   @mask_token.setter
   def 				__lowercase						(   self   ,    lowercase)     ->		str:







          '''simple docstring'''

          a__		:      int					=							AddedToken(UpperCamelCase__   ,    lstrip=UpperCamelCase__   ,    rstrip=UpperCamelCase__) if isinstance(UpperCamelCase__   ,    UpperCamelCase__) else value
          a__		:      List[Any]					=							value

   def 				__lowercase						(   self   ,    *lowercase   ,    **lowercase)     ->		Tuple:







          '''simple docstring'''

          a__		:      Dict					=							kwargs.get('is_split_into_words'   ,    UpperCamelCase__)

          if is_split_into_words and not self.add_prefix_space:
                 raise ValueError(
                     F'You need to instantiate {self.__class__.__name__} with add_prefix_space=True '
                     'to use it with pretokenized inputs.')

          return super()._batch_encode_plus(*UpperCamelCase__   ,    **UpperCamelCase__)

   def 				__lowercase						(   self   ,    *lowercase   ,    **lowercase)     ->		Optional[Any]:







          '''simple docstring'''

          a__		:      Union[str, Any]					=							kwargs.get('is_split_into_words'   ,    UpperCamelCase__)

          if is_split_into_words and not self.add_prefix_space:
                 raise ValueError(
                     F'You need to instantiate {self.__class__.__name__} with add_prefix_space=True '
                     'to use it with pretokenized inputs.')

          return super()._encode_plus(*UpperCamelCase__   ,    **UpperCamelCase__)

   def 				__lowercase						(   self   ,    lowercase   ,    lowercase = None)     ->		List[Any]:







          '''simple docstring'''

          a__		:      Optional[Any]					=							self._tokenizer.model.save(UpperCamelCase__   ,    name=UpperCamelCase__)
          return tuple(UpperCamelCase__)

   def 				__lowercase						(   self   ,    lowercase   ,    lowercase=None)     ->		int:







          '''simple docstring'''

          a__		:      List[Any]					=							[self.bos_token_id] + token_ids_a + [self.eos_token_id]
          if token_ids_a is None:
                 return output

          return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]

   def 				__lowercase						(   self   ,    lowercase   ,    lowercase = None)     ->		List[str]:







          '''simple docstring'''

          a__		:      str					=							[self.sep_token_id]
          a__		:      List[Any]					=							[self.cls_token_id]

          if token_ids_a is None:
                 return len(cls + token_ids_a + sep) * [0]
          return len(cls + token_ids_a + sep + sep + token_ids_a + sep) * [0]










'''simple docstring'''







import cmath
import math


def       __UpperCamelCase					(      lowercase_       :  float   ,       lowercase_       :  float   ,       lowercase_       :  float   ,       lowercase_       :  float   ):
       """simple docstring"""




       a_						     =			math.radians(lowercase_   )
       a_						     =			math.radians(lowercase_   )

       # Convert voltage and current to rectangular form
       a_						     =			cmath.rect(lowercase_   ,       lowercase_   )
       a_						     =			cmath.rect(lowercase_   ,       lowercase_   )

       # Calculate apparent power
       return voltage_rect * current_rect


if __name__ == "__main__":
  import doctest

  doctest.testmod()




